{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "fd6edbbf",
   "metadata": {},
   "source": [
    "# <center><font face=\"楷体\" color=\"lightblue\">策略复现</font></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d41d6b9",
   "metadata": {},
   "source": [
    "#### <center><font face=\"宋体\" color=\"orange\">天津大学——马梓航</font></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "005de3f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import h5py\n",
    "import torch\n",
    "from scipy.stats import spearmanr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90a24bc8",
   "metadata": {},
   "source": [
    "##### **1.重写Dataset**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d24aa59",
   "metadata": {},
   "source": [
    "> 实现逻辑：重写__init__、\\_\\_len\\_\\_、\\_\\_getitem\\_\\_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "49236358",
   "metadata": {},
   "outputs": [],
   "source": [
    "#重写dataset类\n",
    "class StockDataset(torch.utils.data.Dataset):\n",
    "    def __init__(self, h5_path):\n",
    "        with h5py.File(h5_path, 'r') as f:\n",
    "            self.x1 = f['x1_daily'][:]\n",
    "            self.x2 = f['x2_weekly'][:]\n",
    "            self.x3 = f['x3_monthly'][:]\n",
    "            self.y = f['y'][:]\n",
    "            self.codes_dates = f['codes_dates'][:]\n",
    "\n",
    "        # 借鉴的思路\n",
    "        # 将数据转化为float提示GPU计算效率\n",
    "        self.x1 = self.x1.astype(np.float32)\n",
    "        self.x2 = self.x2.astype(np.float32)\n",
    "        self.x3 = self.x3.astype(np.float32)\n",
    "        self.y = self.y.astype(np.float32)\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return (\n",
    "            torch.tensor(self.x1[idx]),\n",
    "            torch.tensor(self.x2[idx]),\n",
    "            torch.tensor(self.x3[idx]),\n",
    "            torch.tensor(self.y[idx]),\n",
    "            self.codes_dates[idx]\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1719d6e2",
   "metadata": {},
   "source": [
    "##### **2.自定义collate_fn**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b065f3f",
   "metadata": {},
   "source": [
    "> 实现逻辑：创建嵌套dict，最后逐日期加到list中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d1955e85",
   "metadata": {},
   "outputs": [],
   "source": [
    "def custom_collate(batch):\n",
    "    date_dict = {}\n",
    "    for x1, x2, x3, y, codes_date in batch:\n",
    "        date = codes_date[1]\n",
    "        if date not in date_dict:\n",
    "            date_dict[date] = {\n",
    "                'x1': [],\n",
    "                'x2': [],\n",
    "                'x3': [],\n",
    "                'y': [],\n",
    "                'codes_date': []\n",
    "            }\n",
    "        date_dict[date]['x1'].append(x1)\n",
    "        date_dict[date]['x2'].append(x2)\n",
    "        date_dict[date]['x3'].append(x3)\n",
    "        date_dict[date]['y'].append(y)\n",
    "        date_dict[date]['codes_date'].append(codes_date)\n",
    "\n",
    "    batches = []\n",
    "    for date in date_dict:\n",
    "        x1_batch = torch.stack(date_dict[date]['x1'])\n",
    "        x2_batch = torch.stack(date_dict[date]['x2'])\n",
    "        x3_batch = torch.stack(date_dict[date]['x3'])\n",
    "        y_batch = torch.stack(date_dict[date]['y'])\n",
    "        codes_date_batch = np.stack(date_dict[date]['codes_date'])\n",
    "        batches.append((x1_batch, x2_batch, x3_batch, y_batch, codes_date_batch))\n",
    "\n",
    "    return batches"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12992ebf",
   "metadata": {},
   "source": [
    "##### **3.主网络**"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "cc8bf9ea",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ceb8216e",
   "metadata": {},
   "source": [
    "> 实现逻辑如图：很简单的模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2870cf17",
   "metadata": {},
   "outputs": [],
   "source": [
    "class SharedGRUModel(torch.nn.Module):\n",
    "    def __init__(self):\n",
    "        super(SharedGRUModel, self).__init__()\n",
    "\n",
    "        # 共享GRU模块（知识共享！）\n",
    "        self.shared_gru = torch.nn.GRU(input_size=6, hidden_size=30, batch_first=True)\n",
    "\n",
    "        # 批标准化层（独立）\n",
    "        self.bn1 = torch.nn.BatchNorm1d(30)\n",
    "        self.bn2 = torch.nn.BatchNorm1d(30)\n",
    "        self.bn3 = torch.nn.BatchNorm1d(30)\n",
    "\n",
    "        # 任务特定全连接层\n",
    "        self.fc1 = torch.nn.Linear(30, 1)  # 日频子任务\n",
    "        self.fc2 = torch.nn.Linear(30, 1)  # 周频子任务\n",
    "        self.fc3 = torch.nn.Linear(30, 1)  # 月频子任务\n",
    "\n",
    "    def forward(self, x1, x2, x3):\n",
    "        # 共享GRU处理不同频率数据\n",
    "\n",
    "        _, h1 = self.shared_gru(x1)  # 日频\n",
    "        _, h2 = self.shared_gru(x2)  # 周频\n",
    "        _, h3 = self.shared_gru(x3)  # 月频\n",
    "\n",
    "        # 独立批标准化\n",
    "        h1 = self.bn1(h1.squeeze(0))\n",
    "        h2 = self.bn2(h2.squeeze(0))\n",
    "        h3 = self.bn3(h3.squeeze(0))\n",
    "\n",
    "        # 子任务预测\n",
    "        y1 = self.fc1(h1).squeeze(-1)\n",
    "        y2 = self.fc2(h2).squeeze(-1)\n",
    "        y3 = self.fc3(h3).squeeze(-1)\n",
    "\n",
    "        # 等权合成\n",
    "        y_pred = (y1 + y2 + y3) / 3\n",
    "        return y_pred, y1, y2, y3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6f8303c",
   "metadata": {},
   "source": [
    "##### **4.训练逻辑**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca8c40db",
   "metadata": {},
   "source": [
    "> 实现逻辑：损失函数的构建，第一次接触自定义自定义损失函数的项目（这是重点）"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "c95592d8",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a63492c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "class IC_Correlation_Loss(torch.nn.Module):\n",
    "    def __init__(self, lambda_val=0.01):\n",
    "        super(IC_Correlation_Loss, self).__init__()\n",
    "        self.lambda_val = lambda_val\n",
    "\n",
    "    def forward(self, y_true, y1, y2, y3):\n",
    "        # 计算IC项（使用皮尔逊相关系数近似）\n",
    "        def pearson_corr(x, y):\n",
    "            # 将x和y堆叠成一个二维张量\n",
    "            stacked = torch.stack([x, y], dim=0)\n",
    "            corr_matrix = torch.corrcoef(stacked)\n",
    "            return corr_matrix[0, 1]\n",
    "\n",
    "        ic1 = pearson_corr(y1, y_true)\n",
    "        ic2 = pearson_corr(y2, y_true)\n",
    "        ic3 = pearson_corr(y3, y_true)\n",
    "\n",
    "        # 计算子任务间相关性惩罚项\n",
    "        corr12 = pearson_corr(y1, y2)\n",
    "        corr13 = pearson_corr(y1, y3)\n",
    "        corr23 = pearson_corr(y2, y3)\n",
    "\n",
    "        # 损失函数计算\n",
    "        loss = - (ic1 + ic2 + ic3) + self.lambda_val * (corr12 + corr13 + corr23)\n",
    "        return loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0580ec1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_model(model, train_loader, val_loader, epochs=100, early_stop=10):\n",
    "    optimizer = torch.optim.Adam(model.parameters(), lr=0.005)\n",
    "    criterion = IC_Correlation_Loss(lambda_val=0.01)\n",
    "    # criterion.cuda()\n",
    "\n",
    "    best_val_ic = -np.inf\n",
    "    early_stop_counter = 0\n",
    "\n",
    "    for epoch in range(epochs):\n",
    "        model.train()\n",
    "        train_loss = 0.0\n",
    "        for sub_batch in train_loader:\n",
    "            for x1, x2, x3, y, codes_dates in sub_batch:\n",
    "                x1 = cross_sectional_scale(x1)\n",
    "                x2 = cross_sectional_scale(x2)\n",
    "                x3 = cross_sectional_scale(x3)\n",
    "\n",
    "                x1 = torch.tensor(x1)\n",
    "                x2 = torch.tensor(x2)\n",
    "                x3 = torch.tensor(x3)\n",
    "\n",
    "                # x1.cuda()\n",
    "                # x2.cuda()\n",
    "                # x3.cuda()\n",
    "                # y.cuda()\n",
    "                # codes_dates.cuda()\n",
    "\n",
    "                optimizer.zero_grad()\n",
    "                _, y1, y2, y3 = model(x1, x2, x3)\n",
    "                loss = criterion(y, y1, y2, y3)#前向计算损失\n",
    "                loss.backward()#反向计算梯度\n",
    "                optimizer.step()#梯度更新\n",
    "                train_loss += loss.item()\n",
    "\n",
    "        # 验证集评估（使用IC）\n",
    "        model.eval()\n",
    "        val_ics = []\n",
    "        with torch.no_grad():\n",
    "            for sub_batch in val_loader:\n",
    "                for x1, x2, x3, y, codes_dates in sub_batch:\n",
    "                    x1 = cross_sectional_scale(x1)\n",
    "                    x2 = cross_sectional_scale(x2)\n",
    "                    x3 = cross_sectional_scale(x3)\n",
    "\n",
    "                    x1 = torch.tensor(x1)\n",
    "                    x2 = torch.tensor(x2)\n",
    "                    x3 = torch.tensor(x3)\n",
    "                    \n",
    "\n",
    "                    y_pred, _, _, _ = model(x1, x2, x3)\n",
    "                    val_ic = spearmanr(y_pred.cpu().numpy(), y.cpu().numpy())[0]\n",
    "                    val_ics.append(val_ic)\n",
    "\n",
    "        avg_val_ic = np.nanmean(val_ics)  # 处理可能的NaN\n",
    "\n",
    "        print(f'Epoch {epoch + 1} | Train Loss: {train_loss / len(train_loader):.4f} | Val IC: {avg_val_ic:.4f}')\n",
    "\n",
    "        # 早停机制（基于IC提升）\n",
    "        if avg_val_ic > best_val_ic:\n",
    "            best_val_ic = avg_val_ic\n",
    "            early_stop_counter = 0\n",
    "            torch.save(model.state_dict(), 'data/best_shared_gru_model_month.pth')\n",
    "        else:\n",
    "            early_stop_counter += 1\n",
    "            if early_stop_counter >= early_stop:\n",
    "                print(f'Early stopping triggered at epoch {epoch + 1}')\n",
    "                break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aff94456",
   "metadata": {},
   "source": [
    "##### **5.预测逻辑**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a809e34",
   "metadata": {},
   "outputs": [
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m在当前单元格或上一个单元格中执行代码时 Kernel 崩溃。\n",
      "\u001b[1;31m请查看单元格中的代码，以确定故障的可能原因。\n",
      "\u001b[1;31m单击<a href='https://aka.ms/vscodeJupyterKernelCrash'>此处</a>了解详细信息。\n",
      "\u001b[1;31m有关更多详细信息，请查看 Jupyter <a href='command:jupyter.viewOutput'>log</a>。"
     ]
    }
   ],
   "source": [
    "def predict_model(model, val_loader):\n",
    "    torch.load('data/best_shared_gru_model_month.pth')\n",
    "    model.eval()\n",
    "    val_ics = []\n",
    "    res = pd.DataFrame()\n",
    "    with torch.no_grad():\n",
    "        for sub_batch in val_loader:\n",
    "            for x1, x2, x3, y, codes_dates in sub_batch:\n",
    "\n",
    "                # x1.cuda()\n",
    "                # x2.cuda()\n",
    "                # x3.cuda()\n",
    "                # y.cuda()\n",
    "                # codes_dates.cuda()\n",
    "\n",
    "                res_tmp = pd.DataFrame()\n",
    "                y_pred, y1, y2, y3 = model(x1, x2, x3)\n",
    "                val_ic = spearmanr(y_pred.cpu().numpy(), y.cpu().numpy())[0]\n",
    "                val_ics.append(val_ic)\n",
    "                res_tmp[\"code\"] = codes_dates[:, 0]\n",
    "                res_tmp[\"date\"] = codes_dates[:, 1]\n",
    "                res_tmp[\"y\"] = y\n",
    "                res_tmp[\"y_factor\"] = y_pred\n",
    "                res_tmp[\"y1\"] = y1\n",
    "                res_tmp[\"y2\"] = y2\n",
    "                res_tmp[\"y3\"] = y3\n",
    "                res = pd.concat([res, res_tmp])\n",
    "    avg_val_ic = np.nanmean(val_ics)  # 处理可能的NaN\n",
    "    res[res[\"date\"] == b'2025-01-27']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d363aa08",
   "metadata": {},
   "source": [
    "##### **6.主程序**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83d602fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cross_sectional_scale(x):\n",
    "    \"\"\"每日横截面上对所有股票标准化\"\"\"\n",
    "    # x: (batch_size, seq_len, features)\n",
    "    mean = x.mean(axis=0, keepdims=True)\n",
    "    std = x.std(axis=0, keepdims=True)\n",
    "    return (x - mean) / (std + 1e-8)\n",
    "\n",
    "train_dataset = StockDataset('data/stock_data_train_month.h5')\n",
    "val_dataset = StockDataset('data/stock_data_test_month.h5')\n",
    "\n",
    "train_loader = torch.utils.data.DataLoader(\n",
    "        train_dataset,\n",
    "        batch_size=5000,\n",
    "        shuffle=False,\n",
    "        pin_memory=True,  # 加速GPU数据传输\n",
    "        collate_fn=custom_collate  # 使用自定义的 collate_fn\n",
    "        )\n",
    "\n",
    "val_loader = torch.utils.data.DataLoader(\n",
    "        val_dataset,\n",
    "        batch_size=3000,\n",
    "        shuffle=False,\n",
    "        pin_memory=True,\n",
    "        collate_fn=custom_collate  # 使用自定义的 collate_fn\n",
    "        )\n",
    "\n",
    "#创建模型\n",
    "model=SharedGRUModel()\n",
    "# model.cuda()\n",
    "\n",
    "#训练模型\n",
    "# train_model(model,train_loader,val_loader)\n",
    "\n",
    "#模型预测\n",
    "predict_model(model, val_loader)"
   ]
  }
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